The adaptive immune system produces an enormous variety of antibodies (Ab) and T-cell receptors (TCR) available to respond to the vast array of microorganisms encountered in the environment, as well as to dysregulated self-components. These antigen receptors are key components of both recognition and effector functions, identifying and neutralizing pathogens. Vaccines against a particular pathogen work by inducing protective immunity via these antigen receptors in individuals who have never been exposed to that pathogen. When the regulation of the immune system malfunctions, antigen receptors with reactivity against components of the body may be deployed, resulting in autoimmune disease, such as Type-1 diabetes or Multiple Sclerosis. Finally, therapeutic Abs and TCR are being developed that can be used to treat autoimmune diseases or attack cancer cells. Because of all of these connections to health and disease, understanding the production of these antigen receptors is critical to biomedical research and clinical care. Although the body produces huge numbers of antigen receptors in response to infection or vaccination, or during an autoimmune disease, until recently we could only sequence a few hundred of these sequences from any individual. Now due to the development of deep or next-generation sequencing, it is possible to obtain millions of these sequences from a given subject. Since understanding the response dynamics is essential, it is important to compare these massive sequences at multiple time points for each individual as well as to compare samples across individuals. There are substantial impediments to sharing these data and to comparative analyses more generally. First, the data are voluminous, and there is no repository that is able to manage them appropriately. There is no exchange format or protocol that would facilitate a more decentralized approach. Furthermore, the data are most informative in the context of data from other sources, such as gene expression profiles and clinical data. Thus, issues of confidentiality, consent, and security are must be addressed. Legal and ethical questions, such as intellectual property and ownership, and the privacy and interests of vulnerable populations such as HIVinfected individuals must be also be considered. We believe that these questions must be discussed by the community of interested parties as a whole. In pursuit of this goal, we propose a set of meetings, each of which will consist mainly of focused workshops, designed to address the challenges involved in obtaining, storing, analyzing comparing and sharing these large antigen-receptor repertoire datasets produced by NGS. This meeting grant from NIH would support the first of the larger community meetings bringing together about 100 experts in the fields of immunology, statistics, immunogenetics, data security, service and protection of vulnerable populations, IP and legal issues involved in large genetic databases, and other experts to develop common protocols and standards for this field.